Top 10 Make alternatives for building AI automation

Make (formerly Integromat) is a leading solution in the business workflow automation space. With a large number of SaaS integrations and a very intuitive no-code workflow builder approach, they have positioned themselves as the go-to automation builder for many. Personally, I have used it extensively for various integrations, and it's super good.

Need for alternatives for Make.com

At times, you need very complex and highly customised workflows. Let's suppose you're building an AI product that requires integrations with Salesforce, HubSpot, Google Sheets, Gmail, and other services. You would need more customisation, more control, and an infrastructure that grows as your product grows.

Also, Make has been great for B2B SaaS automation, but it is not a product for developers looking to build applications on top of it. It lacks an SDK, a CLI, and a platform that allows you to create workflows with programming languages. With programming, you get maximum freedom to build anything you wish. Of course, the learning curve is high, but for robust product building, this is the only way.

In this article, I have compiled a list of all the solutions available on the market for building AI-powered automations. I have also included no-code and low-code alternatives.

Top Make alternatives in a nutshell.

If you've somewhere else to be, here is a summary of all the solutions.

For Developers

• Composio: Connect your AI agent with 500+ apps and APIs using one SDK, fully managed auth and enterprise-ready.

• Pipedream: Build, run, and deploy AI workflows in seconds with code-level control.

• Merge: Unified API for syncing data and integrations across categories.

• Nango: Developer infra for managing 500+ API integrations.

• Paragon: Add prebuilt or custom integrations to your product fast.

For Non-Developers

• Zapier: No-code automation with 8,000+ app connections.

• Rube: Hosted MCP server that connects your AI tools to 500+ apps.

• n8n: Open-source automation platform with full flexibility.

• Langflow: Low-code AI builder for RAG and multi-agent apps.

• Gumloop: No-code platform to create AI workflows visually.

How did we evaluate the solutions?

I visited each website, its documentation, and cookbooks, and tried to make the same AI-powered automation across the solutions.

For developer-focused alternatives, I built the same code agent with GitHub, Jira and Slack integrations across all the solutions. Every time a PR is merged, the agent updates the Jira ticket and updates the #tech channel in Slack.

For non-developer alternatives, I built a workflow that conducts in-depth research on the internet and social media platforms, finding relevant leads, and inputs them into a Google Sheet.

The primary evaluation criterion is how easy it is to navigate documents and get started, as well as the reliability of the tools (Are they accurate? How many correct tool calls, and how effective is authentication handling, etc)

Developer Friendly Alternatives

1. Composio

ℹ️ Developer-first platform to connect AI agents with 500+ apps, APIs, and workflows.

Composio is built for developers who want to connect their AI agent with 500+ apps, APIs, and workflows. It's a developer-first platform and a bridge that gives your agent access to hundreds of SaaS apps, APIs, and workflows out of the box.

Composio handles everything from building integrations, managing authentication per integration, to optimising JSON schema for agents, all of this in one call.

Instead of manually building connectors for integrations (Slack, Notion, you name it...), you drop in Composio's SDK or API, and your agent can start taking action right away.

With Composio, you can:

• Add over 100 ready-to-use integrations to your AI agent instantly.

• Expose APIs and tools in a structured way for LLMs (Claude, GPT, Gemini, etc.) to consume.

• Deploy production-ready agents faster without reinventing the wheel.

• A dedicated dashboard for monitoring all the tool activities.

• Extend workflows by mixing prebuilt connectors with your own custom logic.

• Access the MCP servers of all the SaaS APIs to use them with your favourite AI assistant (Chatgpt, Claude, Cursor, VSCode, etc)

• There's a lot...

How did it fare in tests?

This was the most seamless experience from the developer's perspective. Up-to-date docs and APIs made it a breeze to build the agent without any hassle. The tools were highly flexible and reliable to work with, and out of 10 executed workflows, it worked all the time. So, 10//10.

Instead of wiring up OAuth, rate limits, and sync logic yourself, Composio handles that for you.

Check out the docs to get started, or jump straight in by installing their SDK in your project.

Quick Start:

# Install SDK (TypeScript)
npm install @composio/core

# or (Python)

Check out this demo to see Composio in action for Python. 👇

For TypeScript, refer to this: Getting Started with Composio using TypeScript

💁 NOTE: There’s Rube which is a part of Composio if you’re looking for somewhat similar for non-developers which I’ll cover in the next section.

2. Pipedream

Pipedream gives you a visual workflow builder and lets you drop into code when you want to. It’s built for developers who wish to speed without losing control.

Here’s what makes Pipedream valuable:

• It supports 2,800+ apps and APIs so that you can link your AI agents to many tools quickly.

• You can write custom logic in Node.js, Python, Go, or Bash inside workflows whenever you need flexibility.

• It handles OAuth, tokens, and integrations so you don’t have to reinvent those standard parts.

• For AI-heavy tasks, Pipedream offers code generation from prompts, making it easier to spin up agent logic.

How did it perform on the test?

Pipedream has the most extensive collection of integrations among all. That's a huge plus. The Pipedream connector is very intuitive to work with. While it is excellent for building everyday workflows, I found the docs to be an afterthought for AI-related workflows. Examples were hard to find. Overall, a mixed experience for a developer unfamiliar with the SDK.

Check out this quick demo to see Pipedream in action. 👇

3. Merge

Merge is all about simplifying integration. Instead of building connectors one by one, you use a single unified API. Combine that with their MCP (Model Context Protocol) support, and your AI agent can read/write across multiple systems without requiring manual integration wiring.

Here’s how Merge helps you:

• It encompasses various categories, including accounting, ticketing, CRM, file storage, and more, all utilising a standard data model.

• You embed the Merge Link to let users link their accounts with apps you support. It handles auth, permissions, etc.

• The MCP server from Merge lets your AI agent treat all those integrations as “tools” it can call via MCP.

• Merge gives you SDKs, sandboxes, and developer tools to build faster without reinventing everything.

• Merge's agent handler lets you add tools to AI agents.

How did it fare in tests?

They have recently launched an agent handler, which repurposes their integrations for AI workflows. I liked the fact that they have a dedicated separate docs for AI tools. However, I believe it lacks depth in examples. I usually get started with examples. You can access app tools via MCP, which I find a bit limiting and useless for a highly customised solution.

Want to get a quick video overview? Here you go, the CEO Shensi Ding herself explains how Merge helps. 👇

4. Nango

Nango is all about giving developers infrastructure so they don't have to build every connector from scratch. It provides tools and building blocks to manage auth, syncing, webhooks, and custom logic, all with full control over how data flows.

I don't see much advantage to using Nango over other tools I've mentioned, but it's worth giving a shot.

What Nango lets you do:

• Ship integrations to 500+ APIs quickly with prebuilt templates, auth handling, rate-limit logic, and more.

• Write Functions (TypeScript code) that run inside Nango for custom logic: data transformations, webhook handling, or special API quirks.

• Sync data both ways (read & write), manage webhooks, and handle complex API workflows.

• Self-host locally or use Nango’s cloud, with architecture built for reliability, observability, and scale.

How did it fare in tests?

A perfect solution. It has good docs, but mostly focuses on traditional integrations and actions. They have done pretty well at Docs for building AI agents. However, you can feel this is an afterthought. But it's really good, but it's on the expensive side, so it might cost you a little more if you hang around a lot.

Here’s an intro video demo to Nango. 👇

5. Paragon

Paragon is a tool that helps you quickly add integrations to your product. It comes with 130+ ready-made connectors, and you can also build your own custom ones on the same platform.

Here’s what Paragon gives you:

• It handles authentication, token refresh, and API quirks so you don’t have to.

• You can use its Custom Integration Builder to create new connectors in minutes when a prebuilt one doesn’t exist.

• It supports embedding the Connect UI (for users linking accounts) or operating headless, providing full control.

• Your integration logic can run as workflows (with retries, debugging, and concurrency) or in TypeScript for when custom code is needed.

How did it fare in tests?

Paragon has been a player in this space for a while. But, I find the docs for a new user to be a bit unintuitive. They have a good number of tools optimised for AI agents. Additionally, it was somewhat challenging to navigate the documentation for getting up to speed. Regardless, the agent did work albeit a frictional developer experience.

Here's a quick video intro to Paragon. 👇

For Non-Developers

1. Zapier

Zapier is a veteran in the automation game, and now it’s evolving fast into an AI orchestration tool too. You build workflows (called “Zaps”) that let actions in one app trigger responses in another (no coding needed, as you guessed it 😉).

With Zapier, you can:

• Automate repetitive tasks across multiple apps (Slack, Gmail, CRMs, etc.)

• Use AI functions to route or act on data mid-workflow

• Build “Interfaces” (custom forms/UIs) that feed into Zaps

• Use “Tables” as lightweight databases for your workflows

And because Zapier supports thousands of apps, chances are the tools you already use are already supported.

Sounds cool? Here's a quick tutorial to get your hands on Zapier. 👇

2. Rube

If you’ve come across the term MCP before, you know it stands for Model Context Protocol. In simple terms, it’s a bridge that lets AI models talk to external apps and services, giving them both data and the ability to take action.

Rube acts as a hosted MCP server that bundles integrations with popular tools like Slack, Gmail, Facebook, and many more. Instead of setting up servers and wiring APIs yourself, you instantly unlock access to over 500 apps right inside your AI chat tools.

To see what’s available, you can browse the Rube marketplace, which lists all the supported apps.

Getting started is simple:

• Install Rube on your preferred platform, or

• Sign up on the web app, connect an app, and test it directly in your browser.

Here’s a quick demo that shows Rube in action 👇

3. n8n

n8n is an open-source platform that makes it easy to create automation workflows, AI agents, and integrations without heavy coding. You get a visual canvas where you drag and connect nodes to link apps, APIs, and logic together.

The best part? It’s completely free and open-source. You can run it on your own machine, deploy it in the cloud, or use their hosted version if you want a plug-and-play option.

With n8n, you can:

• Connect hundreds of apps and databases right out of the box

• Add JavaScript or Python when you need advanced custom logic

• Build one-off automations or scale up to production-grade workflows

• Automate almost anything that exposes an API

In short, if there’s an API, chances are you can automate it with n8n. 🤯

If you want to see what’s possible, check out this quick walkthrough from NetworkChuck. It’s a great introduction to how powerful n8n can be 👇

4. Langflow

Langflow gives you a drag-and-drop visual interface that lets you build complex AI workflows without writing every line of code.

Under the hood, it’s powered by Python and gives you full access to customise components, hook into APIs, or integrate vector stores.

You can:

• Quickly iterate using visual flows and reusable components

• Orchestrate multi-agent systems with conversation control and retrieval logic

• Turn your flows into APIs, JSON exports, or even MCP servers for integration

• Support major LLMs, databases, and tools out of the box

• As always, there's a lot more...

Take a look at the Langflow docs to learn more.

Here's a quick intro video to Langflow 👇

5. Gumloop

Gumloop works similarly to Rube or n8n, providing a visual canvas where you link building blocks (called “nodes”) to design workflows.

You place triggers, logic, API calls, AI prompts, or integrations on a canvas, connect them, and deploy. It handles orchestration behind the scenes.

What you can do with Gumloop:

• Build workflows that fetch data, call AI models, transform it, and push results to applications like Google Sheets, Slack, CRMs, and more.

• Use subflows to reuse chunks of logic within larger flows.

• Integrate with services like Slack, Salesforce, Airtable, Outlook, GitHub, Google, and more.

• Use its built-in AI features to scrape websites, analyse content, generate text, etc., all inside flows.

Want to see it in action? Here’s a demo showing a real workflow built using Gumloop 👇

These are your top 10 Make alternative AI automation tools for 2025, and that wraps up this article. Thank you so much for reading! 🫡